Homec4science
Diffusion pypulseq (master) Browse

pypulseq/pypulseq/add_ramps.py
7542b39630c1master

Last Change
Raw File

add_ramps.py
View Options

from copy import copy
from types import SimpleNamespace
from typing import Union, List
import numpy as np
from pypulseq.calc_ramp import calc_ramp
from pypulseq.opts import Opts
def add_ramps(k: Union[list, np.ndarray, tuple], system=Opts(), rf: SimpleNamespace = None, max_grad: int = 0,
max_slew: int = 0) -> List[np.ndarray]:
"""
Adds segment so that `k` k-space trajectory ramps up from 0 to `k[0]` and ramps down from `k[-1]` to 0. If `k` is a
tuple or list of k-space trajectories, ramp-ups and ramp-downs are added to each.
Parameters
----------
k : array_like
Array-like of k-space trajectories to add ramp-ups and -downs to.
system : Opts, optional, default=Opts()
System limits.
rf : SimpleNamespace, optional
Zeros are added to this pulse sequence event over the ramp times in `k`.
max_grad : int, optional, default=0
Maximum gradient amplitude.
max_slew : int, optional, default=0
Maximum slew rate.
Returns
-------
result : list[
List of ramped up and ramped down k-space trajectories from `k`.
Raises
------
ValueError
If `k` is not list, np.ndarray or tuple
RuntimeError
If gradient ramps fail to be calculated
"""
if not isinstance(k, (list, np.ndarray, tuple)):
raise ValueError(f'k has to be one of list, np.ndarray, tuple. Passed: {type(k)}')
k_arg = copy(k)
if max_grad > 0:
system.max_grad = max_grad
if max_slew > 0:
system.max_slew = max_slew
k = np.vstack(k)
num_channels = k.shape[0]
k = np.vstack((k, np.zeros((3 - num_channels, k.shape[1]))))
k_up, ok1 = calc_ramp(np.zeros((3, 2)), k[:, :2], system)
k_down, ok2 = calc_ramp(k[:, -2:], np.zeros((3, 2)), system)
if not (ok1 and ok2):
raise RuntimeError('Failed to calculate gradient ramps')
k_up = np.hstack((np.zeros((3, 2)), k_up))
k_down = np.hstack((k_down, np.zeros((3, 1))))
k = np.hstack((k_up, k, k_down))
result = []
if not isinstance(k_arg, list):
result.append(k[:num_channels])
else:
for i in range(num_channels):
result.append(k[i])
if rf is not None:
result.append(np.concatenate((np.zeros(k_up.shape[1] * 10), rf, np.zeros(k_down.shape[1] * 10))))
return result
c4science · Help